Internet of Restaurants in the New York Times: Rah Rah Data Mining

Last May I went to the annual National Restaurant Association meeting with Bruce Schneier, a well known technologist, and listened to Internet of Things pitches. Here’s what we found:

Some of the sales pitches are compelling: Companies offer to harvest customer data so the restaurant can better track its clientele’s needs. They offer to manage every aspect of a restaurant’s labor force. They offer to turn every piece of kitchen equipment into an “Internet of Things” device, a phrase now used casually in marketing, as if we all agree on its definition. Turn your restaurant into a panopticon! Schneier isn’t surprised, as he’s seen this sort of thing before in other industries. “Much of the ‘Internet of Restaurants,'” as we agree to call it, “is extractive and disempowering while pretending to be about giving control to employees and owners,” he says.

There are basically two models:

1) Extract data from your customers and employees and use it to exploit them.
2) Have your data extracted by your IoT provider and they will monetize it either by trying to dominate the market or by selling it to someone else.

Earlier this week, the New York Times wrote a “rah rah data mining!” piece on IoT in restaurants, largely without skepticism.

The early diners are dawdling, so your 7:30 p.m. reservation looks more like 8. While you wait, the last order of the duck you wanted passes by. Tonight, you’ll be eating something else — without a second bottle of wine, because you can’t find your server in the busy dining room. This is not your favorite night out.

The right data could have fixed it, according to the tech wizards who are determined to jolt the restaurant industry out of its current slump. Information culled and crunched from a wide array of sources can identify customers who like to linger, based on data about their dining histories, so the manager can anticipate your wait, buy you a drink and make the delay less painful.

It can track the restaurant’s duck sales by day, week and season, and flag you as a regular who likes duck. It can identify a server whose customers have spent a less-thanaverage amount on alcohol, to see if he needs to sharpen his second-round skills.

So Big Data is staging an intervention.

Every word choice here is fascinating, because it’s staged as “intervention.” Big Data is not a healthcare provider or a friend trying to “intervene.” It’s written from the PoV of the customer here, for the customer’s benefit, not from the PoV of a business trying to extract your money. And it’s written with no sense of the trade-offs of giving away your data – yours either as customer or or as restaurant.

It’s a riveting example of what Schneier calls “surveillance capitalism,” hyped up here in the paper of record.

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